Multi-vehicle localisation with additive compressed factor graphs

Abstract

This paper introduces a distributed and decentralised method to solve the cooperative localisation problem utilising the factor graph framework. This method enables vehicles to create compact packets of their own sensor information between their involvement in intervehicle measurements. The packets are limited in size, with this size dependent on the size of the state space alone. The number of packets generated is also limited at two packets (one per vehicle) created per intervehicle measurement. The packets and measurements can be shared and propagated to all vehicles not just direct neighbours or to vehicles involved in the measurements. Vehicles maintain a local solver that incorporates all local sensor information and motion updates in full nonlinear form and includes the fixed linearised packets from other vehicles. This local solver is able to update local state variables and relinearise local and intervehicle factors but has to hold remote state variables and packet data at a fixed linearisation point. We show the estimated solution is of a similar quality to a state of the art centralised relinearising estimator iSAM2 and superior to a fixed linearisation filtering solution via comparing RMS error in position estimation in simulation. Consistency of the method is also shown via the NEES metric. Communication requirements for each of the competing methods are shown, with compaction of packets being more useful the larger the ratio between intervehicle and local measurement intervals. The technique is validated using multivehicle simulation and real datasets.

Probabilistic cooperative mobile robot area coverage and its application to autonomous seabed mapping

“…In our approach, we transmit raw data, but we combine measurements together to avoid this backlogging problem. The recent work of Walls et al (2015) and Toohey et al (2014), which were developed in parallel, also solve this problem similarly.…”

Review of mission planning for autonomous marine vehicle fleets

“…As mentioned previously in 6.1, the work by Sotzing and Lane () has successfully enabled vehicles to operate within the limited communication environment, albeit with the risk of vehicles being allocated to the same task (which is resolved once each vehicle establishes contact with the other). Toohey, Pizarro, and Williams () produced a communication method that minimised the bandwidth usage but still allow multiple AUVs to share localisation information with each other. However, for missions that require submerged vehicles to reach a consensus that are within range of each other, noise or multipathing phenomena may cause a Byzantine Failure (see Driscoll, Hall, Paulitsch, Zumsteg and Sivencrona () for a set of Byzantine Failure case studies in avionics).…”